Automatic and Remote Visuo-Mechanics Auditing

1. A computer implemented method (CIM) comprising: opening a data communication session between an end user computer system of a first user and a remote eye test server computer over a communication network, wherein the end user computer system is located in an environment of the first user and is paired with Internet of Things (IoT) devices that contribute to ambient light in the environment; during the data communication session, administering, by the eye test server computer, an automated eye test that tests a set of characteristic(s) relating to vision of the first user; during the administration of the automated eye test, sending, by the eye test server computer, over the communication network and to the end user computer system, an instruction that causes a local analytics engine on the end user computer system to make an adjustment to screen settings of the end user computer system and an adjustment to one or more of the IoT devices to facilitate interactions under different screen settings and ambient light testing conditions; collecting data via one or more sensors in the end user computer system during the administration of the automated eye test under the different screen settings and ambient light testing conditions, the data including: tracking visuo-mechanics of an eye of the first user; proximity of the end user computer system to a face of the first user; and visual settings of the end user computer system; generating a visual profile of the first user including user specific data of the first user based on the administration of the automated the eye test under the different screen settings and ambient light testing conditions; and automatically adjusting a respective one of the IoT devices in the environment of the first user based on the user specific data and current screen brightness settings of the end user computer system, wherein the respective one of the IoT devices comprises a smart lighting system or a smart curtain in the environment of the first user.

2. The CIM of claim 1 further comprising: producing a plurality of inferences, by the local analytics engine, after a calibration period.

3. The CIM of claim 1 further comprising: producing at least one recommendation, by the local analytics engine, after a calibration period.

4. The CIM of claim 1 further comprising: advising an optimal time of day for specific eye test related activities based on at least one of the following: screen brightness and usual ambient light.

5. The CIM of claim 1 further comprising: creating an alert for medical consultation for just in time examination and treatment based on visual performance metrics of the first user deviating from a baseline in the visual profile of the first user and medical guidelines; and uploading logged trends on a local analytics engine to a consolidated database.

6. A computer implemented method (CIM) comprising: opening a data communication session between an end user computer system of a first user and a remote eye test server computer over a communication network; during the data communication session, administering, by the eye test server computer, an automated eye test that tests a set of characteristic(s) relating to vision of the first user; during the administration of the automated eye test, sending, by the eye test server computer, over the communication network and to the end user computer system, an instruction that causes a local analytics engine on the end user computer system to make an adjustment to screen settings of the end user computer system and an adjustment to one or more of the IoT devices to facilitate interactions under different screen settings and ambient light testing conditions; learning a baseline of the first user based on the eye test; altering the baseline based on user specific data; and automatically adjusting a respective one of the IoT devices comprising a smart lighting system in the environment of the first user based on the user specific data and screen brightness settings of the first user computer system in the environment of the first user.

7. A computer implemented method (CIM) comprising: opening a data communication session between an end user computer system of a first user and a remote eye test server computer over a communication network; during the data communication session, administering, by the eye test server computer, an automated eye test that tests a set of characteristic(s) relating to vision of the first user; during the administration of the automated eye test, sending, by the eye test server computer, over the communication network and to the end user computer system, an instruction that causes a local analytics engine on the end user computer system to make an adjustment to screen settings of the end user computer system and an adjustment to one or more of the IoT devices to facilitate interactions under different screen settings and ambient light testing conditions; learning a baseline of the first user based on the eye test; altering the baseline based on user specific data; and automatically adjusting a respective one of the IoT devices comprising a smart curtain in the environment of the first user based on the user specific data and screen brightness settings of the first user computer system in the environment of the first user.

8. The CIM of claim 1, wherein the automatically adjusting the respective one of the IoT devices in the environment of the first user is performed by the local analytics engine.

9. The CIM of claim 8, further comprising the local analytics engine automatically advising the first user of an optimal time of day for a specific activity based on screen brightness and usual ambient light.

10. The CIM of claim 8, wherein the automatically adjusting the respective one of the IoT devices in the environment of the first user comprises dynamically adjusting the respective one of the IoT devices while the first user is moving within a space to provide the first user with preferred lighting settings.